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communication compression

55 papers

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Co-occurring keywords

federated learning (1333) distributed optimization (275) distributed learning (563) error feedback (22) gradient compression (78) communication efficiency (297) stochastic gradient descent (1091) stochastic gradient (296) model compression (3302) distributed training (188)

Papers

Privacy Amplification via Compression: Achieving the Optimal Privacy-Accuracy-Communication Trade-off in Distributed Mean Estimation NIPS 2023
Breaking the Communication-Privacy-Accuracy Tradeoff with $f$-Differential Privacy NIPS 2023
Communication-Efficient Stochastic Gradient Descent Ascent with Momentum Algorithms IJCAI 2023
Compressed-VFL: Communication-Efficient Learning with Vertically Partitioned Data ICML 2022
Communication-Compressed Adaptive Gradient Method for Distributed Nonconvex Optimization AISTATS 2022
QSFL: A Two-Level Uplink Communication Optimization Framework for Federated Learning ICML 2022
SoteriaFL: A Unified Framework for Private Federated Learning with Communication Compression NIPS 2022
Lower Bounds and Nearly Optimal Algorithms in Distributed Learning with Communication Compression NIPS 2022
Communication Acceleration of Local Gradient Methods via an Accelerated Primal-Dual Algorithm with an Inexact Prox NIPS 2022
BEER: Fast $O(1/T)$ Rate for Decentralized Nonconvex Optimization with Communication Compression NIPS 2022
Distributed Online Convex Optimization with Compressed Communication NIPS 2022
DAdaQuant: Doubly-adaptive quantization for communication-efficient Federated Learning ICML 2022
Basis Matters: Better Communication-Efficient Second Order Methods for Federated Learning AISTATS 2022
Correlated Quantization for Distributed Mean Estimation and Optimization ICML 2022
Fine-tuning Language Models over Slow Networks using Activation Quantization with Guarantees NIPS 2022
DRIVE: One-bit Distributed Mean Estimation NIPS 2021
DeepReduce: A Sparse-tensor Communication Framework for Federated Deep Learning NIPS 2021
1-bit Adam: Communication Efficient Large-Scale Training with Adam’s Convergence Speed ICML 2021
CANITA: Faster Rates for Distributed Convex Optimization with Communication Compression NIPS 2021
EF21: A New, Simpler, Theoretically Better, and Practically Faster Error Feedback NIPS 2021
A Linearly Convergent Algorithm for Decentralized Optimization: Sending Less Bits for Free! AISTATS 2021
MARINA: Faster Non-Convex Distributed Learning with Compression ICML 2021
Distributed Second Order Methods with Fast Rates and Compressed Communication ICML 2021
Preserved central model for faster bidirectional compression in distributed settings NIPS 2021
Quantized Compressive Sampling of Stochastic Gradients for Efficient Communication in Distributed Deep Learning AAAI 2020